Research on precise lithium battery state of charge estimation method based on CALSE-LSTM model and pelican algorithm.

This paper presents an innovative fusion model called "CALSE-LSTM," which integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), self-attention mechanisms, and squeeze-and-excitation attention mechanisms to optimize the estimation accuracy of the State of Charge (SoC). The model incorporates battery historical data as input and employs a dual-attention mechanism based on CNN-LSTM to extract diverse features from the input data, thereby enhancing the model's ability to learn hidden information. To further improve model performance, we fine-tune the model parameters using the Pelican algorithm. Experiments conducted under Urban Dynamometer Driving Schedule (UDDS) conditions show that the CALSE-LSTM model achieves a Root Mean Squared Error (RMSE) of only 1.73 % in lithium battery SoC estimation, significantly better than GRU, LSTM, and CNN-LSTM models, reducing errors by 31.9 %, 31.3 %, and 15 %, respectively. Ablation experiments further confirm the effectiveness of the dual-attention mechanism and its potential to improve SoC estimation performance. Additionally, we validate the learning efficiency of CALSE-LSTM by comparing model training time with the number of iterations. Finally, in the comparative experiment with the Kalman filtering method, the model in this paper significantly improved its performance by incorporating power consumption as an additional feature input. This further verifies the accuracy of CALSE-LSTM in estimating the State of Charge (SoC) of lithium batteries.

Glycolytic enzyme PGK1 promotes M1 macrophage polarization and induces pyroptosis of acute lung injury via regulation of NLRP3.

Acute lung injury (ALI) is characterized by an unregulated inflammatory reaction, often leading to severe morbidity and ultimately death. Excessive inflammation caused by M1 macrophage polarization and pyroptosis has been revealed to have a critical role in ALI. Recent study suggests that glycolytic reprogramming is important in the regulation of macrophage polarization and pyroptosis. However, the particular processes underlying ALI have yet to be identified. In this study, we established a Lipopolysaccharide(LPS)-induced ALI model and demonstrated that blocking glycolysis by using 2-Deoxy-D-glucose(2-DG) significantly downregulated the expression of M1 macrophage markers and pyroptosis-related genes, which was consistent with the in vitro results. Furthermore, our research has revealed that Phosphoglycerate Kinase 1(PGK1), an essential enzyme in the glycolysis pathway, interacts with NOD-, LRR- and pyrin domain-containing protein 3(NLRP3). We discovered that LPS stimulation improves the combination of PGK1 and NLRP3 both in vivo and in vitro. Interestingly, the absence of PGK1 reduces the phosphorylation level of NLRP3. Based on in vitro studies with mice bone marrow-derived macrophages (BMDMs), we further confirmed that siPGK1 plays a protective role by inhibiting macrophage pyroptosis and M1 macrophage polarization. The PGK1 inhibitor NG52 suppresses the occurrence of excessive inflammation in ALI. In general, it is plausible to consider a therapeutic strategy that focuses on modulating the relationship between PGK1 and NLRP3 as a means to mitigate the activation of inflammatory macrophages in ALI.

Enantioselective formal total synthesis of dihydrospirotryprostatin B.

Spirotryprostatins are representative members of medicinally interesting bioactive molecules of the spirooxindole natural products. In this communication, we present a novel enantioselective total synthesis of the spirooxindole alkaloid dihydrospirotryprostatin B. The synthesis takes advantage of copper-catalyzed tandem reaction of o-iodoanilide chiral sulfinamide derivatives with alkynone to rapidly construct the key quaternary carbon stereocenter of the natural product dihydrospirotryprostatin B.

Novel lactylation-related signature to predict prognosis for pancreatic adenocarcinoma.

BACKGROUND: Lactate, previously considered a metabolic byproduct, is pivotal in cancer progression and maintaining the immunosuppressive tumor microenvironment. Further investigations confirmed that lactate is a primary regulator, introducing recently described post-translational modifications of histone and non-histone proteins, termed lysine lactylation. Pancreatic adenocarcinomas are characterized by increased glycolysis and lactate accumulation. However, our understanding of lactylation-related genes in pancreatic adenocarcinomas remains limited. AIM: To construct a novel lactylation-related gene signature to predict the survival of patients with pancreatic cancer. METHODS: RNA-seq and clinical data of pancreatic adenocarcinoma (PDAC) were obtained from the GTEx (Genotype-Tissue Expression) and TCGA (The Cancer Genome Atlas) databases via Xena Explorer, and GSE62452 datasets from GEO. Data on lactylation-related genes were obtained from publicly available sources. Differential expressed genes (DEGs) were acquired by using R package "DESeq2" in R. Univariate COX regression analysis, LASSO Cox and multivariate Cox regressions were produced to construct the lactylation-related prognostic model. Further analyses, including functional enrichment, ESTIMATE, and CIBERSORT, were performed to analyze immune status and treatment responses in patients with pancreatic cancer. PDAC and normal human cell lines were subjected to western blot analysis under lactic acid intervention; two PDAC cell lines with the most pronounced lactylation were selected. Subsequently, RT-PCR was employed to assess the expression of LRGs genes; SLC16A1, which showed the highest expression, was selected for further investigation. SLC16A1-mediated lactylation was analyzed by immunofluorescence, lactate production analysis, colony formation, transwell, and wound healing assays to investigate its role in promoting the proliferation and migration of PDAC cells. In vivo validation was performed using an established tumor model. RESULTS: In this study, we successfully identified 10 differentially expressed lactylation-related genes (LRGs) with prognostic value. Subsequently, a lactylation-related signature was developed based on five OS-related lactylation-related genes (SLC16A1, HLA-DRB1, KCNN4, KIF23, and HPDL) using Lasso Cox hazard regression analysis. Subsequently, we evaluated the clinical significance of the lactylation-related genes in pancreatic adenocarcinoma. A comprehensive examination of infiltrating immune cells and tumor mutation burden was conducted across different subgroups. Furthermore, we demonstrated that SLC16A1 modulates lactylation in pancreatic cancer cells through lactate transport. Both in vivo and in vitro experiments showed that decreasing SLC16A1 Level and its lactylation significantly inhibited tumor progression, indicating the potential of targeting the SLC16A1/Lactylation-associated signaling pathway as a therapeutic strategy against pancreatic adenocarcinoma. CONCLUSION: We constructed a novel lactylation-related prognostic signature to predict OS, immune status, and treatment response of patients with pancreatic adenocarcinoma, providing new strategic directions and antitumor immunotherapies.

Chemokines and Their Receptors: Predictors of Therapeutic Potential in Tumor Microenvironment on Esophageal Cancer.

Esophageal carcinoma (ESCA) is an aggressive solid tumor. The 5-year survival rate for patients with ESCA is estimated to be less than 20%, mainly due to tumor invasion and metastasis. Therefore, it is urgent to improve early diagnostic tools and effective treatments for ESCA patients. Tumor microenvironment (TME) enhances the ability of tumor cells to proliferate, migrate, and escape from the immune system, thus promoting the occurrence and development of tumor. TME contains chemokines. Chemokines consist of four major families, which are mainly composed of CC and CXC families. The main purpose of this review is to understand the CC and CXC chemokines and their receptors in ESCA, to improve the understanding of tumorigenesis of ESCA and determine new biomarkers for the diagnosis and prognosis of ESCA. We reviewed the literature on CC and CXC chemokines and their receptors in ESCA identified by PubMed database. This article introduces the general structures and functions of CC, CXC chemokines and their receptors in TME, as well as their roles in the progress of ESCA. Chemokines are involved in the development of ESCA, such as cancer cell invasion, metastasis, angiogenesis, and radioresistance, and are key determinants of disease progression, which have a great impact on patient prognosis and treatment response. In addition, a full understanding of their mechanism of action is essential to further verify that these chemokines and their receptors may serve as biomarkers or therapeutic targets of ESCA.

Identification of qualitative characteristics of immunosuppression in sepsis based on immune-related genes and immune infiltration features.

Objective: Sepsis is linked to high morbidity and mortality rates. Consequently, early diagnosis is crucial for proper treatment, reducing hospitalization, and mortality rates. Additionally, over one-fifth of sepsis patients still face a risk of death. Hence, early diagnosis, and effective treatment play pivotal roles in enhancing the prognosis of patients with sepsis. Method: The study analyzed whole blood data obtained from patients with sepsis and control samples sourced from three datasets (GSE57065, GSE69528, and GSE28750). Commonly dysregulated immune-related genes (IRGs) among these three datasets were identified. The differential characteristics of these common IRGs in the sepsis and control samples were assessed using the REO-based algorithm. Based on these differential characteristics, samples from eight Gene Expression Omnibus (GEO) databases (GSE57065, GSE69528, GSE28750, GSE65682, GSE69063, GSE95233, GSE131761, and GSE154918), along with three ArrayExpress databases (E-MTAB-4421, E-MTAB-4451, and E-MTAB-7581), were categorized and scored. The effectiveness of these differential characteristics in distinguishing sepsis samples from control samples was evaluated using the AUC value derived from the receiver operating characteristic curve (ROC) curve. Furthermore, the expression of IRGs was validated in peripheral blood samples obtained from patients with sepsis through qRT-PCR. Results: Among the three training datasets, a total of 84 common dysregulated immune-related genes (IRGs) were identified. Utilizing a within-sample relative expression ordering (REOs)-based algorithm to analyze these common IRGs, differential characteristics were observed in three reverse stable pairs (ELANE-RORA, IL18RAP-CD247, and IL1R1-CD28). In the eight GEO datasets, the expression of ELANE, IL18RAP, and IL1R1 demonstrated significant upregulation, while RORA, CD247, and CD28 expression exhibited notable downregulation during sepsis. These three pairs of immune-related marker genes displayed accuracies of 95.89% and 97.99% in distinguishing sepsis samples among the eight GEO datasets and the three independent ArrayExpress datasets, respectively. The area under the receiver operating characteristic curve ranged from 0.81 to 1.0. Additionally, among these three immune-related marker gene pairs, mRNA expression levels of ELANE and IL1R1 were upregulated, whereas the levels of CD247 and CD28 mRNA were downregulated in blood samples from patients with sepsis compared to normal controls. Conclusion: These three immune-related marker gene pairs exhibit high predictive performance for blood samples from patients with sepsis. They hold potential as valuable auxiliary clinical blood screening tools for sepsis.

Swarm intelligence based deep learning model via improved whale optimization algorithm and Bi-directional long short-term memory for fault diagnosis of chemical processes.

The chemical production process typically possesses complexity and high risks. Effective fault diagnosis is a key technology for ensuring the reliability and safety of chemical production processes. In this study, a comprehensive fault diagnosis method based on time-varying filtering empirical mode decomposition (TVF-EMD), kernel principal component analysis (KPCA), and an improved whale optimization algorithm (WOA) to optimize bi-directional long short-term memory (BiLSTM) is proposed. This research utilizes TVF-EMD and KPCA to analyze and preprocess the raw data, eliminating noise and and reducing the dimensions of the fault data. Subsequently, BiLSTM is employed for fault data classification. To address the hyperparameters within BiLSTM, the enhanced WOA is used for optimization. Finally, the efficacy and superiority of this approach are validated through two fault diagnosis examples.

Skeleton-Based Activity Recognition for Process-Based Quality Control of Concealed Work via Spatial-Temporal Graph Convolutional Networks.

Computer vision (CV)-based recognition approaches have accelerated the automation of safety and progress monitoring on construction sites. However, limited studies have explored its application in process-based quality control of construction works, especially for concealed work. In this study, a framework is developed to facilitate process-based quality control utilizing Spatial-Temporal Graph Convolutional Networks (ST-GCNs). To test this model experimentally, we used an on-site collected plastering work video dataset to recognize construction activities. An ST-GCN model was constructed to identify the four primary activities in plastering works, which attained 99.48% accuracy on the validation set. Then, the ST-GCN model was employed to recognize the activities of three extra videos, which represented a process with four activities in the correct order, a process without the activity of fiberglass mesh covering, and a process with four activities but in the wrong order, respectively. The results indicated that activity order could be clearly withdrawn from the activity recognition result of the model. Hence, it was convenient to judge whether key activities were missing or in the wrong order. This study has identified a promising framework that has the potential to the development of active, real-time, process-based quality control at construction sites.

Golden bifid treatment regulates gut microbiota and serum metabolites to improve myocardial dysfunction in cecal ligation and puncture-induced sepsis mice.

Myocardial damage is a major consequence and a significant contributor to death in cases of sepsis, a severe infection characterized by a distinct inflammatory response and a potential threat to the patient's life. Recently, the effects of intestinal microbiota and serum metabolites on sepsis have garnered increasing attention. Herein, the effects of golden bifid treatment upon cecal ligation and puncture (CLP)-induced sepsis in mice as a model for myocardial dysfunction were explored. Our results demonstrated that golden bifid treatment partially improved myocardial dysfunction and apoptosis, cardiac inflammation and oxidative stress, and intestinal mucosal permeability and barrier dysfunction in CLP-induced sepsis mice. The intestinal microbiota diversity and abundance were also altered within sepsis mice and improved by golden bifid treatment. Mucispirillum schaedleri, Acinetobacter baumannii and Lactobacullus intestinalis were significantly correlated with heart damage markers, inflammatory factors, or oxidative stress indicators. Serum differential metabolite levels were also significantly correlated with these parameters. Altogether, golden bifid treatment might be an underlying approach for treating sepsis-induced myocardial dysfunction and highlight the underlying effect of intestinal microbiota and serum metabolites on the pathogenesis and treatment of sepsis-triggered myocardial dysfunction.

Histomorphological analysis of perfusion parameters and CNS lymphatic vessels in mice: an experimental method study.

To investigate the distribution and characteristics of lymphatic vessels within the central nervous system, we focus on the meninges of the spinal cord and brain parenchyma in mice. Additionally, we aim to provide experimental methods for obtaining optimal imaging and clear structures of lymphatic vessels, while optimizing the perfusion parameters to improve histomorphological quality. Male C57BL/6J mice were randomly divided into four groups, with each group assigned a specific perfusion parameter based on perfusion volumes and temperatures. Immunofluorescence staining of lymphatics and blood vessels was performed on both meningeal and the brain tissue samples. Statistical analysis was performed using one-way analysis of variance to compare the groups, and a significant level of P < 0.05 was considered statistically significant. Our study reports the presence of lymphatic vessels in the meninges of the spinal cord and brain parenchyma in mice. We highlight the crucial role of high perfusion volume of paraformaldehyde with low temperature in fixation for achieving optimal results. We provide experimental methods for obtaining optimal imaging and clear structures of lymphatic vessels in the meninges of the spinal cord and brain parenchyma in mice, which contribute to our understanding of the distribution and characteristics of lymphatic vessels within the central nervous system. Further research is warranted to explore the functional implications of these lymphatic vessels and their potential therapeutic significance in neurodegenerative and neuroinflammatory diseases.

Inhibition of CISD1 alleviates mitochondrial dysfunction and ferroptosis in mice with acute lung injury.

The NET family member, CDGSH iron-sulfur domain-containing protein 1 (CISD1), is located in theoutermembrane of mitochondria, where it regulates energy and iron metabolism. CISD1 has vital functions in certain human diseases; however, its function in acute lung injury (ALI) is unknown. ALI pathogenesis critically involves mitochondrial dysfunction and ferroptosis, which might be regulated by CISD1. Therefore, we investigated CISD1's function in mitochondrial dysfunction and ferroptosis regulation in lipopolysaccharide (LPS)-induced ALI. We found that CISD1 was upregulated in LPS-induced ALI,and silencing Cisd1 prevented cell apoptosis and increased cell viability. When CISD1was inhibited by mitoNEET ligand-1 (NL-1) there was a significant mitigation of pathological injury and lung edema, and reduced numbers of total cells, polymorphonuclear leukocytes, and a decreased protein content in the bronchoalveolar lavage fluid (BALF). Moreover, inhibition of CISD1 markedly decreased the interleukin (IL)6, IL-1ß, and tumor necrosis factor alpha (TNF-α) levels in the lungs and BALF of ALI-model mice. Silencing of Cisd1 prevented LPS-induced mitochondrial membrane potential depolarization, cellular ATP reduction, and reactive oxygen species (ROS) accumulation, suggesting mitochondrial protection. ALI activated ferroptosis, as evidenced by the increased lipid-ROS, intracellular Fe2+ level, reduced Gpx4 (glutathione peroxidase 4) expression, and the glutathione/glutathione disulfide ratio. Interestingly, inhibition of CISD1 reduced LPS-induced ferroptosis in vivo and in vitro. In conclusion, inhibition of CISD1 alleviated mitochondrial dysfunction and ferroptosis in LPS-induced ALI, identifying CISD1 as possible target for therapy of LPS-induced ALI.

Research and application of a novel selective stacking ensemble model based on error compensation and parameter optimization for AQI prediction.

With the ongoing process of industrialization, the issue of declining air quality is increasingly becoming a critical concern. Accurate prediction of the Air Quality Index (AQI), considered as an all-inclusive measure representing the extent of pollutants present in the atmosphere, is of paramount importance. This study introduces a novel methodology that combines stacking ensemble and error correction to improve AQI prediction. Additionally, the reptile search algorithm (RSA) is employed for optimizing model parameters. In this study, four distinct regional AQI data containing a collection of 34864 data samples are collected. Initially, we perform cross-validation on ten commonly used single models to obtain prediction results. Then, based on evaluation indices, five models are selected for ensemble. The results of the study show that the model proposed in this paper achieves an improvement of around 10% in terms of accuracy when compared to the conventional model. Thus, the model introduced in this study offers a more scientifically grounded approach in tackling air pollution.

Ultrasound microvascular flow imaging combined with vascular endothelial growth factor for diagnosis of fetal growth restriction / 中国医学影像技术

Objective To observe the value of ultrasound microvascular flow imaging(MV-Flow)combined with maternal serum vascular endothelial growth factor(VEGF)expression level for diagnosis of fetal growth restriction(FGR).Methods Totally 87 pregnant women with FGR(FGR group,including 43 cases of gestational week＜28 weeks[＜28 weeks subgroup]and 44 cases of ≥28 weeks[≥28 weeks subgroup])and 112 normal pregnant women with normal fetuses(normal control group,55 with gestational week＜28 weeks[NC 1 subgroup]and 57 with ≥28 weeks[NC 2 subgroup])were prospectively enrolled.MV-Flow technology was used to measure placental microvascular index(MVI),and the placental microvascular circulation was evaluated.The expression level of maternal serum VEGF was detected simultaneously,also of placental maternal surface immediately after delivery.The receiver operating characteristic curves were drawn to explore the value of placental MVI,maternal serum VEGF and the combination of placental MVI,maternal serum VEGF for diagnosing FGR.Results The levels of placental MVI and maternal serum VEGF in 2 subgroups of FGR group were both lower than those in control group(all P＜0.01).Placental VEGF expression level in FGR group was significantly lower than that in control group(P＜0.01).The area under the curve(AUC)of placental MVI,maternal serum VEGF and their combination for diagnosing FGR＜28 weeks was 0.981,0.870 and 0.997,respectively,while for diagnosing FGR≥28 weeks was 0.991,0.867 and 0.993,respectively.AUC of maternal serum VEGF alone for diagnosing in 2 subgroups of FGR were both lower than that of placental MVI and combination of placental MVI and maternal serum VEGF(all P＜0.05),while no significant difference of AUC was found between placental MVI and combination of maternal serum VEGF and placental MVI(both P＞0.05).Conclusion Both placental MVI and maternal serum VEGF level could be used to screen FGR,and the former was more valuable.

Calcium phosphate combined with recombinant human bone morphogenetic protein-2 in repair and reconstruction of tibial infectious bone defects / 中国组织工程研究

BACKGROUND:Although the clinical application of Masquelet technology has achieved extensive success,the research on optimizing all aspects of Masquelet technology is still being carried out.The focus of doctors is to speed up bone healing and shorten bone healing time after bone grafting. OBJECTIVE:To observe the effect of calcium phosphate combined with recombinant human bone morphogenetic protein-2 in repairing tibial infectious bone defects. METHODS:Thirty-one patients with tibial infectious bone defects were selected from The People's Hospital of Jianyang City from June 2017 to June 2022.They were treated with the Masquelet membrane induction technique.During the second stage of operation,they were divided into a control group(n=15)and a study group(n=16)according to different bone graft materials.Patients in the control group were implanted with autologous bone/allogeneic bone particles,and those in the study group were implanted with calcium phosphate combined with recombinant human bone morphogenetic protein-2/autologous bone particles.Six months after the second stage operation,peripheral blood inflammatory indexes such as white blood cell count,C-reactive protein,and erythrocyte sedimentation rate were detected.Imaging bone healing time,bone healing X-ray score,bone defect healing classification,and adjacent joint function were recorded.The presence of nail track infection,implant absorption,pain,and infection in the bone extraction area were observed. RESULTS AND CONCLUSION:(1)White blood cell count,erythrocyte sedimentation rate,and C-reactive protein levels of the two groups 6 months after the second stage operation were significantly lower than those before the first stage operation(P<0.05).There was no significant difference in each index between the two groups(P>0.05).(2)Bone healing time in the study group was shorter than that in the control group(P<0.05).(3)The Samantha X-ray score of the study group 6 months after the second stage operation was higher than that of the control group(P<0.05).The excellent and good rate of bone defect healing and adjacent joint function of the study group was higher than that of the control group(P<0.05).There was no significant difference in the recurrence rate and complication rate between the two groups(P>0.05).(4)These findings indicate that the effect of calcium phosphate combined with recombinant human bone morphogenetic protein-2 during the second stage operation of the Masquelet membrane induction technique in the treatment of tibial infectious bone defect is good and safe.

miR-133b Promotes Esophageal Squamous Cell Carcinoma Metastasis.

Background: Evaluation of biological changes at the molecular level has important clinical implications for improving the survival rate of esophageal squamous cell carcinoma (ESCC). Therefore, we plan to analyze and elucidate the expression of microRNA-133b (miR-133b), M2 pyruvate kinase (PKM2), and signal transducer and activator of transcription 3 (STAT3) in ESCC and their associated clinicopathological significance. Methods: The 72 patients with ESCC were selected as the experimental study group. Normal adjacent tissues (NAT) were matched as the control group. In this study, in situ hybridization was used to detect the expression of miR-133b in ESCC, and tissue expressions of PKM2 and STAT3 were detected by immunohistochemistry, and literature review was conducted. Results: Studies had shown that the positive expression of miR-133b in NAT was significantly higher than that in ESCC (χ2 = 9.007, P = .003). PKM2 and STAT3 in ESCC had a significantly higher positive expression levels than those of NAT (χ2 = 56.523, P = .000; χ2 = 72.939, P = .000). From correlation analysis, there was a negative correlation between miR-133b and PKM2(r = -0.515, P < .001), a negative correlation between miR-133b and STAT3(r = -0.314, P = .007), and a positive correlation between PKM2 and STAT3(r = 0.771, P < .001). Conclusions: In ESCC, our study demonstrated that downregulation of miR-133b and upregulation of PKM2 and STAT3. We predict that miR-133b may inhibit the STAT3 pathway by downregulating PKM2.

Inhibition of SIRT6 aggravates p53-mediated ferroptosis in acute lung injury in mice.

Although studies have shown that protein 53 (p53)-mediated ferroptosis is involved in acute lung injury (ALI), the mechanism of its regulation remains unclear. The protective effects of Sirtuin 6 (SIRT6), a histone deacetylase, have been demonstrated in multiple diseases; however, further studies are needed to elucidate the role of SIRT6 in ALI. In the present study, we hypothesize that SIRT6 protects against lipopolysaccharide (LPS)-induced ALI by regulating p53-mediated ferroptosis. We observed that the inhibition of ferroptosis prevented LPS-induced ALI. The knockout of p53 blocked LPS-induced ferroptosis and ALI, suggesting that p53 facilitated ALI by promoting ferroptosis. In addition, the inhibition of SIRT6 aggravated LPS-induced ferroptosis and ALI, while the depression of ferroptosis blocked the exacerbation of lung injury induced by SIRT6 inhibition. The results suggest that SIRT6 protects against ALI by regulating ferroptosis. Furthermore, the inhibition of SIRT6 reinforced the p53 acetylation and the deletion of p53 rescued the exacerbation of ferroptosis induced by SIRT6 inhibition. The findings indicate that SIRT6 regulates the acetylation of p53 and prevents p53-mediated ferroptosis. In conclusion, our results indicate that SIRT6 protects against LPS-induced ALI by regulating p53-mediated ferroptosis, thereby demonstrating that SIRT6 holds great promise as a therapeutic target for ALI.

Pyroptosis: the dawn of a new era in endometrial cancer treatment.

Endometrial cancer (EC) is a malignancy of the inner epithelial lining of the uterus. While early-stage EC is often curable through surgery, the management of advanced, recurrent and metastatic EC poses significant challenges and is associated with a poor prognosis. Pyroptosis, an emerging form of programmed cell death, is characterized by the cleavage of gasdermin proteins, inducing the formation of extensive gasdermin pores in the cell membrane and the leakage of interleukin-1ß (IL-1ß) and interleukin-18 (IL-18), consequently causing cell swelling, lysis and death. It has been found to be implicated in the occurrence and progression of almost all tumors. Recent studies have demonstrated that regulating tumor cells pyroptosis can exploit synergies function with traditional tumor treatments. This paper provides an overview of the research progress made in molecular mechanisms of pyroptosis. It then discusses the role of pyroptosis and its components in initiation and progression of endometrial cancer, emphasizing recent insights into the underlying mechanisms and highlighting unresolved questions. Furthermore, it explores the potential value of pyroptosis in the treatment of endometrial cancer, considering its current application in tumor radiotherapy, chemotherapy, targeted therapy and immunotherapy.

Antibacterial lanostane triterpenoids from Ganoderma tsugae.

A phytochemical investigation on the 80% EtOH extract of the fruiting bodies of Ganoderma tsugae resulted into the isolation of two previously undescribed lanostane triterpenoids, 7,11-dioxo-3ß-acetyloxy-26,27-dihydroxy-lanosta-8,24-diene (1) and 7,20-dioxo-3ß-acetyloxy-11ß,15α-dihydroxy-22,23,24,25,26,27-hexanorlanosta-8-ene (2), togeher with one known lanostane triterpenoid ganodermanontriol (3). Structural elucidation of all the compounds were performed by spectral methods such as 1D and 2D (1H-1H COSY, HMQC, and HMBC) NMR spectroscopy. All the triterpenoids were in vitro evaluated for their antibacterial activities against six pathogenic microorganisms. Compound 3 exhibited some activities against three Gram positive bacteria with MIC values less than 30 µg/ml.

Identification of ferroptotic genes and phenotypes in idiopathic nonobstructive azoospermia.

Effective treatments for nonobstructive azoospermia (NOA), which affects 1% of all men globally, are limited by undefined pathogenic mechanisms, especially in idiopathic NOA (iNOA). Here, we tried to identify the functional ferroptosis-related genes and phenotypes involved in iNOA. Differentially expressed ferroptotic genes were identified from iNOA mRNA microarray datasets by bioinformatic analyses, and these ferroptotic genes were subsequently filtered by various algorithms. Then, receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic ability of the abovementioned genes for iNOA. Generally, 11 differentially expressed ferroptotic genes were downregulated, and five genes were upregulated in iNOA samples. Four genes, including DUSP1, GPX4, HSD17B11, and SLC2A8, were technically selected and determined to be potential biomarkers for iNOA. Subsequently, similar expression levels were validated at both the RNA and protein levels in the iNOA specimens. Finally, morphologic and biochemical assays were applied to define the ferroptotic phenotypes in testes. The ferroptotic features, like shrunken mitochondria with electron-dense membranes and a reduction in cristae were observed across various cell types within iNOA patients, accompanied by the overload of ferrous ions and increased lipid peroxidation production. Our findings demonstrated that these ferroptosis genes could be involved in the underlying pathogenesis mechanisms of iNOA by regulating ferroptosis and serve as potential diagnostic biomarkers. Also, the ferroptotic phenotypes were identified in iNOA patients.

Association between the Triglyceride-Glucose Index and Non-Alcoholic Fatty Liver Disease in patients with Atrial Fibrillation.

BACKGROUND: The triglyceride and glucose index (TyG), as a surrogate of insulin resistance (IR), is closely associated with non-alcoholic fatty liver disease (NAFLD). However, the association between the TyG index and NAFLD in atrial fibrillation (AF) is unknown. Therefore, the purpose of this study is to explore the association between the TyG index and NAFLD in AF. METHODS: This retrospective study was performed at Nanchang University's Second Affiliated Hospital. The AF patients who were hospitalized from January 2021 to December 2022 were enrolled. The association between the TyG index and NAFLD in AF patients was assessed by logistic regression and restricted cubic spline analysis. The ability of TyG index for identifying NAFLD was estimated by the area under the receiver operating characteristic (ROC). RESULTS: In this study, 632 people participated in the final analysis, with 176 (27.84%) having NAFLD. In the full adjustment model, there is an association between the TyG index and NAFLD [per 1 unit increment; odds ratios (ORs): 3.28; 95% confidence interval (CI) 2.14, 5.03]. Compared to the lowest tertile (TyG index < 8.29), the ORs for the highest tertile (TyG index ≥ 8.82) were 4.15 (95%CI: 2.28, 7.53). Dose-response analysis showed that the TyG index and NAFLD have a nearly linear relationship (P non-linear = 0.71). The area under the curve (AUC) of the TyG index is 0.735. CONCLUSIONS: Our findings showed a significant association between the TyG index and NAFLD. The TyG index may be a good marker for predicting NAFLD in AF patients.